[Pkg-exppsy-maintainers] Q: Crossvalidation feature selection

[Per B. Sederberg]

Hi Folks:

Wow!  I'm totally amazed with the amazing work you have done on
pymvpa.  I just started using it for real tonight and I'm quite happy.

I'm on a bit of a time constraint (I have a big talk in two weeks) and
could use a pointer here and there so that I can analyze my latest
data.

I've gotten a long way based on my tracking the code, reading the
manual, and examining the searchlight example, but I'm still missing a
couple key steps.

1) I'd like to run feature selection (I'm happy to use anything in
there, such as the ANOVA or something fancier) on each training set of
a N-Fold cross validation run.  I'd also like to save the mask of
those features for later analysis.  Ideally, I'd like to specify a
constant number of features (say 1000) to keep for each fold.

2) I'd like to keep the classifier predictions and values for each
test sample of each fold.  This, too, for later inspection.

3) I'd like to know what is going on a little better.  How do I turn
up a higher level of verbosity so that, for example, it tells me which
fold it's currently on in the crossvalidation or which sphere it's on
in the searchlight?

4) I'm training on subsets of a recall period, but it would be great
to test on every sample from the left-out chunk, returning the
predictions and values for each sample.

Ok, that's all for now.

Thanks for any help,
Per